Faculty Recruiting Support CICS

Postdoctoral Research Associate - Information Fusion Lab

About UMass Amherst

UMass Amherst, the Commonwealth's flagship campus, is a nationally ranked public research university offering a full range of undergraduate, graduate and professional degrees. The University sits on nearly 1,450-acres in the scenic Pioneer Valley of Western Massachusetts, and offers a rich cultural environment in a bucolic setting close to major urban centers. In addition, the University is part of the Five Colleges (including Amherst College, Hampshire College, Mount Holyoke College, and Smith College), which adds to the intellectual energy of the region.


Job Summary

We are inviting applications for a postdoctoral position in machine learning for healthcare in the Information Fusion Lab at UMass Amherst. Our project, 4Thought, aims to address one of the biggest needs in Alzheimer's disease research, an ability for the early diagnosis of this disease.  Currently the disease progresses for many years prior to a diagnosis making it much more difficult to find therapeutic treatments for a significantly advanced disease. We propose to develop novel diagnostic technology based on brain structural MRIs, cognitive test scores and biomarkers. The postdoctoral researcher will be part of a team developing cutting-edge techniques for Alzheimer's Disease forecasting, using hybrid deep learning methodology that leverages complex, multimodal data and domain knowledge. We are also geared towards establishing a startup venture, with our efforts supported by the UMass Institute for Applied Sciences. We thus welcome researchers with entrepreneurial interests and experience.


Essential Functions

  • Introduce new machine learning techniques to forecast Alzheimer's disease from multimodal, multi-visit subject data, including cognitive test scores, brain MRIs and other clinical data.
  • Optimize estimates of information theoretical metrics to boost the feature extraction module from brain MRI images.
  • Contribute to the development of a multi-stage screening pipeline for AD clinical trials, where each stage involves data collected with increasing levels of invasiveness, from questionnaires to MRIs to blood samples and spinal taps.
  • Show that the technology is broadly applicable by performing extensive performance evaluation of analysis of data from different fMRI devices under a variety of settings.
  • Publish papers in top tier venues in the field.
  • Collaborate with and mentor PhD and MS students.
  • Depending on interests, contribute to other ongoing projects in the lab.



  • PhD in a computational field such as Machine Learning, Computer Science, Data Sciences, (Bio)Statistics, Medical Informatics, Mathematics, or a related field.
  • Strong research background in machine learning, statistics, probabilistic modeling, artificial intelligence or a related field.
  • Publications in top-tier venues, any of the following: NeurIPS, ICML, CVPR, ICCV, IJCAI, AAAI, AI Stats, ICLR, JMLR.
  • Expertise in deep learning.
  • Knowledge of statistical analysis techniques.
  • Ability to work independently in a highly collaborative and interdisciplinary environment.
  • Excellent oral and written communications skills.
  • Track record of publications in AI for healthcare venues (MLHC, MICCAI, AMIA etc) or medical conferences/journals is preferred.
  • Expertise in medical imaging is preferred.
  • Experience with python (pytorch/tensorflow) is preferred.
  • Interest in transitioning technology out of the lab for real-world applications is preferred.


Salary Information

  • Salary starts at $65,000 per annum. Salary is negotiable and will depend on qualifications and experience.


Additional Information

  • Flexible start date.
  • The position is for a maximum term of 2 years, with a review after one year. During its term, your appointment is contingent upon satisfactory performance and the existence of funding.
  • Working from home may be possible under certain circumstances, though the postdoc may be expected  to relocate to Massachusetts in the future.
  • The postdoc will have the opportunity, if they so choose, to get involved in translational efforts, participate in entrepreneurial programs such as the NSF iCorps and contribute to grant proposal development.  
  • The postdoc will have the opportunity to participate in entrepreneurial programs such as the NSF iCorps program and other venture development efforts.
  • The postdoc will also be encouraged to enroll in some of the many career development programs available at UMass Amherst, in the areas of career preparation, communication, grants and fellowships, personal development, and teaching https://www.umass.edu/graduate/professional-development/postdoctoral-scholars.


About the Information Fusion Lab

The Information Fusion Lab focuses on machine learning for multimodal, heterogeneous data, particularly from the health domain. Specifically, the lab researches techniques that can combine images, time series and structured data, and can introduce domain-specific saliency into the models. The Information Fusion Lab encompasses expertise on a wide range of ML methods, including deep learning, ensemble learning, object recognition, transfer of causal models and normalizing flows. The target applications include modeling trajectories for chronic conditions such as Alzheimer's disease and osteoarthritis, medical imaging, clinical outcome prediction for critical care applications and assurance of fairness in health across multiple populations.


About the College of Information and Computer Sciences

CICS is internationally recognized for its research activities and has one of the highest ranked and most competitive graduate programs in the nation. With over 40 faculty affiliated with the Center for Data Science, the College is distinguished by its culture of collaboration and leadership in multidisciplinary research. The department is #11 in AI and #20 in Computer Science in the US, according to the US News graduate schools ranking system.


About the Institute of Applied Life Sciences 

IALS was established in 2014 and its mission is translating fundamental research into innovative product candidates, technologies, and services that deliver benefits to human health and well-being. IALS has launched more than 30 Core Facilities - that facilitate a wide range of projects, from device prototyping, precision manufacturing and roll-to-roll fabrication, to human motion and gait studies, calorimetry, magnetic resonance imaging and spectroscopy, as well as, EEG and sleep studies.


Application Instructions

For informal inquiries about this position, please contact Dr. Madalina Fiteraumfiterau@cs.umass.edu 

To apply, follow this link: https://careers.umass.edu/amherst/en-us/job/507451/postdoctoral-research-associate-information-fusion-lab 

To be considered, please submit your CV, a cover letter of 2 pages maximum, a full list of publications, and the contact information of 3 recommenders using the link above.

For full consideration, please apply by April 30th 2021. We will start reviewing applications soon after the deadline and will continue reviewing candidates until the position is filled. Interviews will be conducted remotely. International applicants are welcome.


UMass Amherst is committed to a policy of equal opportunity without regard to race, color, religion, gender, gender identity or expression, age, sexual orientation, national origin, ancestry, disability, military status, or genetic information in employment, admission to and participation in academic programs, activities, and services, and the selection of vendors who provide services or products to the University.  To fulfill that policy, UMass Amherst is further committed to a program of affirmative action to eliminate or mitigate artificial barriers and to increase opportunities for the recruitment and advancement of qualified minorities, women, persons with disabilities, and covered veterans.  It is the policy of the UMass Amherst to comply with the applicable federal and state statutes, rules, and regulations concerning equal opportunity and affirmative action.